Journal ArticleDOI
Tracking Suicide Risk Factors Through Twitter in the US
Jared Jashinsky,Scott H. Burton,Carl L. Hanson,Josh West,Christophe Giraud-Carrier,Michael D. Barnes,Trenton Argyle +6 more
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TLDR
Twitter may be a viable tool for real-time monitoring of suicide risk factors on a large scale and demonstrates that individuals who are at risk for suicide may be detected through social media.Abstract:
Background: Suicide is a leading cause of death in the United States. Social media such as Twitter is an emerging surveillance tool that may assist researchers in tracking suicide risk factors in real time. Aims: To identify suicide-related risk factors through Twitter conversations by matching on geographic suicide rates from vital statistics data. Method: At-risk tweets were filtered from the Twitter stream using keywords and phrases created from suicide risk factors. Tweets were grouped by state and departures from expectation were calculated. The values for suicide tweeters were compared against national data of actual suicide rates from the Centers for Disease Control and Prevention. Results: A total of 1,659,274 tweets were analyzed over a 3-month period with 37,717 identified as at-risk for suicide. Midwestern and western states had a higher proportion of suicide-related tweeters than expected, while the reverse was true for southern and eastern states. A strong correlation was observed between sta...read more
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Proceedings ArticleDOI
Discovering Shifts to Suicidal Ideation from Mental Health Content in Social Media
TL;DR: This paper develops a statistical methodology to infer which individuals could undergo transitions from mental health discourse to suicidal ideation, and utilizes semi-anonymous support communities on Reddit as unobtrusive data sources to infer the likelihood of these shifts.
Journal ArticleDOI
Personal Sensing: Understanding Mental Health Using Ubiquitous Sensors and Machine Learning.
TL;DR: A layered, hierarchical model for translating raw sensor data into markers of behaviors and states related to mental health is provided, focused principally on smartphones, but also including studies of wearables, social media, and computers.
Journal ArticleDOI
Detecting suicidality on Twitter
Bridianne O'Dea,Stephen Wan,Philip J. Batterham,Alison L. Calear,Cecile Paris,Helen Christensen +5 more
TL;DR: This project was supported in part by funding from the NSW Mental Health Commission and the NHMRC John Cade Fellowship 1056964.
Proceedings ArticleDOI
From ADHD to SAD: Analyzing the Language of Mental Health on Twitter through Self-Reported Diagnoses
TL;DR: A broad range of mental health conditions in Twitter data is examined by identifying self-reported statements of diagnosis and language differences between ten conditions with respect to the general population, and to each other are systematically explored.
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